missCompare R package - intuitive missing data imputation framework
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Updated
Dec 2, 2020 - R
missCompare R package - intuitive missing data imputation framework
An R package to apply affine and similarity transformations on vector layers (sp objects)
Leave-one-out Cross-validation for regression models
R code for exchange rate prediction using Multilayer Perceptron (MLP) models with various architectures and evaluation metrics
Forecasting time series data using ARIMA models. Used covariance matrix to find dependencies between stocks.
This is a group project for MTH416A: Regression Analysis at IIT Kanpur
Predictive machine learning model guessing the admissions percentage at a university given directory and financial aid information. Part of the capstone for HarvardX's Data Science certification.
Applied Least Square, Ridge and Lasso regression models to predict the number of comments a blog post will receive
To explore supervised machine learning
Supervised Machine Learning algorithms for Regression in R and Python
HarvardX: PH125.9x: Data Science - Capstone Movielens Project
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